Amir discusses a method to optimize motion processing by evaluating the significance of residuals. By implementing a small neural network alongside convolutions, the system can intelligently decide which computations are necessary, enhancing performance while minimizing unnecessary processing. This approach is particularly effective in scenarios where background movements may generate misleading residuals that don't impact the primary task, such as human pose estimation.
